1. Background—Field of the Invention
The present invention relates generally to information processing systems that are used to detect and isolate anomalies (or fault detection and isolation—FDI), and more specifically to an information processing system that monitors motion-related sensors to accurately detect and isolate the presence of thruster faults. Whereas FDI is a broad field, this invention presents a solution that is especially valuable when certain aspects are present: (1) when the faults that may appear are discrete and finite in number; (2) faults occur and appear abruptly and are not intermittent; (3) the effect of the faults are intermittently present (active) or absent (inactive) at known times; (4) the measurements of these effects are imprecise due to the complexity of the governing physics and presence of sensor noise and disturbances. Although the invention has applicability beyond, it was developed to solve a problem with these attributes: the detection (determining that a fault has occurred) and isolation (determining the exact type and location of the fault) of hard, abrupt, spacecraft thruster faults using only information from existing navigation sensors such as gyroscopes (gyros), accelerometers, star trackers, video cameras, sun sensors, horizon sensors, or other instruments whose output is affected by motions of the spacecraft.
The solution approach falls under the classification of model-based diagnosis; in which models of the system in its nominal and (multiple) failed conditions are used to generate predictions of the system state variables or sensor outputs. Calculation and analysis of the deviations of the measurements from predicted values is performed to detect and isolate the correct fault mode from the list of possible modes.
2. Background—Prior Art
R. Isermann, in “Process Fault Detection Based on Modeling and Estimation Methods—A Survey,” Automatica, Vol. 20, No. 4, pp. 387-404, 1984, presents several FDI approaches that perform well on a variety of applications. However, the on-off nature of the thrusters present in the class of applications addressed here limits the viability of many general-purpose methods. For example, if a thruster has failed off, it will appear to be working correctly at all times that it is not commanded to fire. The present invention presents a general approach for this class of problems.
The most common approach to detect and isolate spacecraft thruster faults is to install pressure, temperature, and electrical sensors at the thrusters. The use of these additional sensors makes the FDI logic very simple and robust, since they can more directly detect when a thruster is producing thrust. However, the need for additional sensors adds to the cost, complexity, mass, and volume requirements of the spacecraft. This type of system is used, for example, on NASA's Space Shuttle Orbiter. If such extensive sensing is not possible, most systems do not have automatic on-line thruster FDI capability.
Deyst, J. J. and Deckert, J. C. proposed, and developed in simulation, a maximum-likelihood based approach for detecting leaking thrusters for the Space Shuttle orbiter's RCS jets in “Maximum likelihood failure detection techniques applied to the Shuttle RCS jets,” Journal of Spacecraft and Rockets, vol. 13, no. 2, 65-74, February 1976. The method for detecting soft failures was also extended to detect hard RCS jet failures. It was tested and found to not have sufficient tolerance for model uncertainty and sensor noise to provide acceptable accuracy for example applications. However, the maximum-likelihood method presented in that work serves as the core upon which this invention builds, increasing the accuracy by using information from all prior time.
Lee, A. Y. and Brown, M. J. developed “A model-based thruster leakage monitor for the Cassini spacecraft,” In Proceedings of the American Control Conference, 1998, vol. 2, pp 902-904, 1998. Unlike the present invention, this was aimed at detecting constant leaks, not failures that would cause varying effects depending on whether the thrusters are commanded to fire or not.
Wilson, E. and Rock, S. M., in “Reconfigurable control of a free-flying space robot using neural networks,” Proceedings of the American Control Conference, Seattle Wash., June 1995, developed an FDI method based on exponentially weighted recursive least squares estimation using accelerometer and angular rate sensors. As with the approach of Deyst and Deckert, this approach was found to have limited accuracy, as compared to the system presented here.